Report NEP-CMP-2023-02-20

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report:

• Al-Haschimi, Alexander & Apostolou, Apostolos & Azqueta-Gavaldon, Andres & Ricci, Martino, 2023, "Using machine learning to measure financial risk in China," Working Paper Series, European Central Bank, number 2767, Jan.
• Dangxing Chen & Luyao Zhang, 2023, "Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance," Papers, arXiv.org, number 2301.07060, Jan.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2023, "ddml: Double/debiased machine learning in Stata," Papers, arXiv.org, number 2301.09397, Jan, revised Jan 2024.
• Jianjun Chen & Yongming Li & Ariel Neufeld, 2023, "Quantum Monte Carlo algorithm for solving Black-Scholes PDEs for high-dimensional option pricing in finance and its complexity analysis," Papers, arXiv.org, number 2301.09241, Jan, revised Nov 2025.
• Elisa Luciano & Matteo Cattaneo & Ron Kenett, 2023, "Adversarial AI in Insurance: Pervasiveness and Resilience," Papers, arXiv.org, number 2301.07520, Jan.
• María Victoria Landaberry & Kenji Nakasone & Johann Pérez & María del Pilar Posada, 2022, "A predictive model of sovereign investment grade using machine learning and natural language processing," Documentos de trabajo, Banco Central del Uruguay, number 2022005.
• Luca Eduardo Fierro & Federico Giri & Alberto Russo, 2023, "Inequality-Constrained Monetary Policy in a Financialized Economy," LEM Papers Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number 2023/05, Jan.
• Bilgin, Rumeysa, 2023, "The Selection Of Control Variables In Capital Structure Research With Machine Learning," SocArXiv, Center for Open Science, number e26qf, Jan, DOI: 10.31219/osf.io/e26qf.
• Ola, Aranuwa Felix, 2023, "Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by non-human animals and humans," OSF Preprints, Center for Open Science, number 8f59d, Jan, DOI: 10.31219/osf.io/8f59d.
• Pinski, Marc & Benlian, Alexander, 2023, "AI Literacy - Towards Measuring Human Competency in Artificial Intelligence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 135990.
• Tom, Daniel M. Ph.D., 2023, "Eliminating Disparate Treatment in Modeling Default of Credit Card Clients," OSF Preprints, Center for Open Science, number cfyzv, Jan, DOI: 10.31219/osf.io/cfyzv.
• Ola, Aranuwa Felix, 2023, "Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—," OSF Preprints, Center for Open Science, number 37m9k, Jan, DOI: 10.31219/osf.io/37m9k.
• Anastasios Petropoulos & Vassilis Siakoulis & Konstantinos P. Panousis & Loukas Papadoulas & Sotirios Chatzis, 2023, "Macroeconomic forecasting and sovereign risk assessment using deep learning techniques," Papers, arXiv.org, number 2301.09856, Jan.
• Christopher Wimmer & Navid Rekabsaz, 2023, "Leveraging Vision-Language Models for Granular Market Change Prediction," Papers, arXiv.org, number 2301.10166, Jan.
• Jongsub Lee & Hayong Yun, 2023, "Learning Production Process Heterogeneity Across Industries: Implications of Deep Learning for Corporate M&A Decisions," Papers, arXiv.org, number 2301.08847, Jan.
• Nabeel, Rao, 2023, "Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by non-human animals and humans. Example," OSF Preprints, Center for Open Science, number sz7mj, Jan, DOI: 10.31219/osf.io/sz7mj.
• Nabeel, Rao, 2023, "Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by non-human animals and humans. Example," OSF Preprints, Center for Open Science, number qhvak, Jan, DOI: 10.31219/osf.io/qhvak.
• Bruno Bouchard & Adil Reghai & Benjamin Virrion, 2021, "Computation of Expected Shortfall by fast detection of worst scenarios," Post-Print, HAL, number hal-02619589, Mar, DOI: 10.1080/14697688.2021.1880618.
• Gebreel, Alia Youssef, 2023, "Artificial Intelligence in Knowledge Management for Construction-Specific Documents," OSF Preprints, Center for Open Science, number zc8mp, Jan, DOI: 10.31219/osf.io/zc8mp.
• Ramis Khabibullin & Sergei Seleznev, 2022, "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Bank of Russia Working Paper Series, Bank of Russia, number wps104, Dec.
• A. Papanicolaou & H. Fu & P. Krishnamurthy & B. Healy & F. Khorrami, 2023, "An Optimal Control Strategy for Execution of Large Stock Orders Using LSTMs," Papers, arXiv.org, number 2301.09705, Jan, revised Jun 2023.
• Hua, Tan Kian, 2023, "Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by non-human animals and humans," OSF Preprints, Center for Open Science, number 8de57, Jan, DOI: 10.31219/osf.io/8de57.
• Jonathan Proctor & Tamma Carleton & Sandy Sum, 2023, "Parameter Recovery Using Remotely Sensed Variables," NBER Working Papers, National Bureau of Economic Research, Inc, number 30861, Jan.
• Huifang Huang & Ting Gao & Pengbo Li & Jin Guo & Peng Zhang & Nan Du, 2023, "Model Based Reinforcement Learning with Non-Gaussian Environment Dynamics and its Application to Portfolio Optimization," Papers, arXiv.org, number 2301.09297, Jan, revised Mar 2023.
• Michael Mueller-Smith & Benjamin Pyle & Caroline Walker, 2023, "Estimating the Impact of the Age of Criminal Majority: Decomposing Multiple Treatments in a Regression Discontinuity Framework," Working Papers, Center for Economic Studies, U.S. Census Bureau, number 23-01, Jan.
• Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2023, "Taste of home: Birth town bias in Geographical Indications," Economics & Statistics Discussion Papers, University of Molise, Department of Economics, number esdp23089, Feb.
• Nikhil Sahni & George Stein & Rodney Zemmel & David M. Cutler, 2023, "The Potential Impact of Artificial Intelligence on Healthcare Spending," NBER Working Papers, National Bureau of Economic Research, Inc, number 30857, Jan.
• Florian Oswald & Patrick Kofod Mogensen, 2022, "floswald/NumericalMethods," Sciences Po Economics Publications (main), HAL, number hal-03945730, Jul.
• Bergeaud, Antonin & Verluise, Cyril, 2022, "The rise of China's technological power: the perspective from frontier technologies," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 117998, Oct.

Report NEP-CMP-2023-02-20

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report: